trim.mcmc {BayesPIM} | R Documentation |
Subset MCMC draws (burn-in and thinning)
Description
Takes an mcmc.list
object (or a list of MCMC chains) and returns
a new mcmc.list
containing only the specified subset of iterations (from
burnin
to end
) with the specified thinning interval.
Usage
trim.mcmc(obj, burnin = 1, end = nrow(as.matrix(obj[[1]])), thining = 1)
Arguments
obj |
An object of class |
burnin |
A numeric scalar giving the starting iteration of the MCMC
sample to keep. Defaults to |
end |
A numeric scalar giving the last iteration of the MCMC sample
to keep. Defaults to the number of rows in the first chain of
|
thining |
A numeric scalar for the thinning interval. Defaults to |
Details
This function subsets each chain of the input obj
to the
specified iteration indices and creates a new mcmc.list
.
If you have multiple MCMC chains, each chain is trimmed in the same way.
Value
An object of class mcmc.list
, representing the trimmed subset
of the original MCMC draws.
Examples
# Example with a toy mcmc.list
set.seed(123)
x1 <- matrix(rnorm(2000), ncol = 2)
x2 <- matrix(rnorm(2000), ncol = 2)
mcmc_list <- mcmc.list(mcmc(x1), mcmc(x2))
# Trim and thin the chains
trimmed_mcmc <- trim.mcmc(mcmc_list, burnin = 100, end = 800, thining = 5)
summary(trimmed_mcmc)